BIG data - BIG gains? : empirical evidence on the link between big data analytics and innovation


Niebel, Thomas ; Rasel, Fabienne ; Viete, Steffen


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URL: https://ub-madoc.bib.uni-mannheim.de/43706
URN: urn:nbn:de:bsz:180-madoc-437068
Document Type: Working paper
Year of publication: 2017
The title of a journal, publication series: ZEW Discussion Papers
Volume: 17-053
Place of publication: Mannheim
Publication language: English
Institution: Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
MADOC publication series: Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Classification: JEL: D22 , L20 , O33,
Keywords (English): Big data , data-driven decision-making , product innovation , firm-level data
Abstract: This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms’ innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likelihood of a firm becoming a product innovator as well as for the market success of product innovations. These results hold for the manufacturing as well as for the service sector but are contingent on firms’ investment in IT-specific skills. Subsequent analyses suggest that firms in the manufacturing and service sector rely on different data sources and data-related firm practices in order to reap the benefits of big data. Overall, the results support the view that big data analytics have the potential to enable innovation.

Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.




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